/**************************************************************************** * * Copyright (c) 2021 Vivante Corporation * * Permission is hereby granted, free of charge, to any person obtaining a * copy of this software and associated documentation files (the "Software"), * to deal in the Software without restriction, including without limitation * the rights to use, copy, modify, merge, publish, distribute, sublicense, * and/or sell copies of the Software, and to permit persons to whom the * Software is furnished to do so, subject to the following conditions: * * The above copyright notice and this permission notice shall be included in * all copies or substantial portions of the Software. * * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER * DEALINGS IN THE SOFTWARE. * *****************************************************************************/ #include "tim/vx/context.h" #include "tim/vx/graph.h" #include "tim/vx/ops/maxpoolwithargmax.h" #include "gtest/gtest.h" TEST(MaxpoolWithArgmax, shape_3_3_1_fp32_kernel_2_stride_2) { auto ctx = tim::vx::Context::Create(); auto graph = ctx->CreateGraph(); tim::vx::ShapeType in_shape({3, 3, 1}); tim::vx::ShapeType out_shape({2, 2, 1}); tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32, in_shape, tim::vx::TensorAttribute::INPUT); tim::vx::TensorSpec output_spec_indices(tim::vx::DataType::UINT8, out_shape, tim::vx::TensorAttribute::OUTPUT); tim::vx::TensorSpec output_spec_values(tim::vx::DataType::FLOAT32, out_shape, tim::vx::TensorAttribute::OUTPUT); auto input_tensor = graph->CreateTensor(input_spec); auto output_tensor_indices = graph->CreateTensor(output_spec_indices); auto output_tensor_values = graph->CreateTensor(output_spec_values); std::vector in_data = { 1, 2, 3, 4, 5, 6, 7, 8, 9 }; std::vector values_golden = { 5, 6, 8, 9 }; std::vector indices_golden = { 3, 2, 1, 0 }; EXPECT_TRUE(input_tensor->CopyDataToTensor(in_data.data(), in_data.size()*4)); std::array ksize = {2, 2}; std::array stride = {2, 2}; auto op = graph->CreateOperation( tim::vx::PadType::VALID, ksize, stride); (*op).BindInputs({input_tensor}).BindOutputs({output_tensor_values, output_tensor_indices}); EXPECT_TRUE(graph->Compile()); EXPECT_TRUE(graph->Run()); std::vector output_values(4); std::vector output_indices(4); EXPECT_TRUE(output_tensor_values->CopyDataFromTensor(output_values.data())); EXPECT_TRUE(output_tensor_indices->CopyDataFromTensor(output_indices.data())); EXPECT_EQ(values_golden, output_values); EXPECT_EQ(indices_golden, output_indices); } TEST(MaxpoolWithArgmax, shape_4_4_1_uint8_kernel_2_stride_2) { auto ctx = tim::vx::Context::Create(); auto graph = ctx->CreateGraph(); tim::vx::ShapeType in_shape({4, 4, 1}); tim::vx::ShapeType out_shape({2, 2, 1}); tim::vx::Quantization io_quant(tim::vx::QuantType::ASYMMETRIC, 1, 0); tim::vx::TensorSpec input_spec(tim::vx::DataType::UINT8, in_shape, tim::vx::TensorAttribute::INPUT, io_quant); tim::vx::TensorSpec output_spec_indices(tim::vx::DataType::UINT8, out_shape, tim::vx::TensorAttribute::OUTPUT); tim::vx::TensorSpec output_spec_values(tim::vx::DataType::UINT8, out_shape, tim::vx::TensorAttribute::OUTPUT, io_quant); auto input_tensor = graph->CreateTensor(input_spec); auto output_tensor_indices = graph->CreateTensor(output_spec_indices); auto output_tensor_values = graph->CreateTensor(output_spec_values); std::vector in_data = { 1, 2, 3, 3, 4, 5, 6, 6, 7, 8, 9, 9, 10, 11, 12, 12 }; std::vector values_golden = { 5, 6, 11, 12}; std::vector indices_golden = { 3, 2, 3, 2}; EXPECT_TRUE(input_tensor->CopyDataToTensor(in_data.data(), in_data.size())); std::array ksize = {2, 2}; std::array stride = {2, 2}; auto op = graph->CreateOperation( tim::vx::PadType::VALID, ksize, stride); (*op).BindInputs({input_tensor}).BindOutputs({output_tensor_values, output_tensor_indices}); EXPECT_TRUE(graph->Compile()); EXPECT_TRUE(graph->Run()); std::vector output_values(4); std::vector output_indices(4); EXPECT_TRUE(output_tensor_values->CopyDataFromTensor(output_values.data())); EXPECT_TRUE(output_tensor_indices->CopyDataFromTensor(output_indices.data())); EXPECT_EQ(values_golden, output_values); EXPECT_EQ(indices_golden, output_indices); }